1. Centro Europeo di Risonanze Magnetiche
una infrastruttura di ricerca nel Polo Scientifico dell’Università di Firenze
Claudio Luchinat
CERM
Università di Firenze

2. Il Polo Scientifico di Sesto Fiorentino

3. The Magnetic Resonance Center in Florence
700b
Bio-labs
800
950
850ss
900
700
Conference room
Library
400
Workshop
500
Computer room
600
600b
700ss
Department
of Chemistry
(offices, bio-labs,
relaxometer, instruments..)
GENEXPRESS, CRYST, CISM
DaVEB Biobank

4. CERM instrumentation NMR instrumentation 700 MHz WB Cryo 900 MHz
700 MHz (a)
Cryo
700 MHz (b)
Cryo
800 MHz
400 MHz
600 MHz
Cryo 900 MHz
850 MHz WB
Cryo 950 MHz

5. The Magnetic Resonance Center in Florence
Protein structure determination
Methodological advancements in NMR
Solid state NMR
ICT and computational biology
Electron/nuclear relaxation (Relaxometry)
Drug discovery
Structural proteomics
Metabolomics
700b
Bio-labs
800
950
850ss
900
700
Conference room
Library
400
Workshop
500
Computer room
600
600b
700ss
We provide access to European researchers since 1994
New access program Bio-NMR ( ) started September 2010
Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, Goteborg
Department
of Chemistry
(offices, bio-labs,
relaxometer, instruments..)
GENEXPRESS, CRYST, CISM
DaVEB Biobank

6. uno sguardo molecolare sulla salute e sulle malattie
Metabolomica:
uno sguardo molecolare sulla salute e sulle malattie
Claudio Luchinat
CERM
Università di Firenze

7. The Research Centers of FiorGen
CERM
Scientific Campus
Sesto Fiorentino
Biomedical Campus
Careggi

8. Scientific Publications
146 publications on high level journals, starting from 2004
Independent reviewers attested the high scientific level of the Foundation
“The scientific production of FiorGen is quite impressive”
Prof. Arturo Falaschi
Scuola Normale Superiore – Pisa
Distinguished Scientist ICGEB Trieste
Aprile 2008
“The scientific productivity of FiorGen is of excellent level”
Prof. Giuseppe Novelli
Tor Vergata University of Rome
University of Arkansas (USA)
WPQ PGx EMEA (UK)
Maggio 2008

9. What is Metabolomics?
Metabolomics is a further “omic” science that is now emerging with the purpose of “elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites in an organism or cell”.
Genomics tells you what could happen. Metabolomics tells you what has happened. Only a few thousand metabolites.
!! However, not negligible external variability !! (source of noise) 9 9

10. Examples of metabolitesH P y r u v i c a d S n x l o e t
Acetyl CoA

11. + Metabolomics Study of small molecules in biological fluids
Metabolic fingerprint

12. 1H NMR spectrum of ethanol__ |

13. 1H NMR spectrum (upfield part) of human urine

14. 1H NMR spectrum (downfield part) of human urine

15. 2 Routes to Metabolomics (fingerprinting and pattern recognition)
Two approaches:
Identify as many metabolites as possible
Use the whole spectrum as a fingerprint (statistics) 1 2 3 4 5 6 7
ppm
Quantitative
methods
Chemometric methods
(fingerprinting and pattern recognition)
-25
-20
-15
-10 -5 5 10 15 20 25
-30
PC1
PC2 1 2 3 4 5 6 7
ppm
hippurate
urea
allantoin
creatinine
2-oxoglutarate
citrate
TMAO
succinate
fumarate
water
taurine

16. The fingerprint Metabolomics: Traditional clinical analysis:
Few already known metabolites for some disease (e.g. glucose for diabetes, etc…)
All metabolites are analyzed together without prior knowledge 16

17. The fingerprint
What are they doing ? 17

18. The fingerprint
Only an analysis at a global level can tell the whole story 18

19. METabolomic REFerence
Ind 1
Ind 2 19 19

20. METabolomic REFerence
Ind 1
Ind 2 20 20

21. METabolomic REFerence
Convex hulls of 22 donors in the three most significant PCA-CA dimensions
PCA for data reduction
CA for obtain well separated clusters
KNN for classification
99% accuracy in montecarlo cross validation
“natural” gender discrimination
MALE
FEMALE
Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008, 105,

22. The signature of Our Body
There exists an individual human metabolic phenotype (metabotype)
The metabotype consists of a variable part (environment) and an invariant part (genetics + environment)
The invariant part persists for at least two-three years (if the diet is averaged using collection of multiple samples)
The discovery of the existence of individual metabotypes is the baseline for Biomedical Researches
Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008
Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009

23. Metabolomics @CERM/CIRMMP
Collaborative Projects
SPIDIA (7th framework program)
Standardization and improvement of pre-analytical procedures for in-vitro diagnostics.
CHANCE (7th framework program)
Evaluation of the impact of nutritional criticalities in population at risk of poverty using NMR metabolomics.
livSYSiPS (ErasysBio+)
The sistem biology of network stress based on data generated from in vitro differentiated hepatocytes derived from individual-specific human iPS cells.
ITFoM (FET Flagship Initiative)
The aim of ITFoM is to develop models of human pathways, tissues, and ultimately of the whole human, to create a “virtual patient” which will enable physicians to identify personalised prevention schedules and treatments adapted to each person.
Progetto COSMOS (EU Coordination action)
To develop new standard for metabolomics sutdies
Progetto BioMedBridges (EU Coordination action)
To develop a unified framework for biomedical studies in Europe
Progetto Melanoma (Ente Cassa di Risparmio di Firenze)
New strategies for diagnosis prognosis and treatment of melanoma.

24. Metabolomics @CERM/CIRMMP
Collaborations
Celiac Disease (Prof. Antonio Calabrò, Careggi Hospital)
Geriatric patients (Dr. Laura Biganzoli, Prato Hospital)
Diabetes in young (Dr. Sonia Toni, Mayer Children’s Hospital)
BPCO (Dr. Massimo Miniati, Careggi Hospital and CNR Pisa)
Metastatic Colorectal Cancer (Dr. Benny W. Jensen, Herlev Hospital, Copenhagen)
Periodonitis (Dr. Mario Aimetti, University of Turin)
Bladder and Prostate Cancer (Dr. Marco Carini, Careggi Hospital)
Cardiovascular Risk (Dr. Adriana Tognaccini, Pistoia Hospital and AVIS Toscana)
Intestinal Bowel Diseases (Prof. Maurizio Vecchi, University of Milan)
Heart Failure (Prof. Franco Gensini, University of Florence)
Breast Cancer (Dr. Angelo Di Leo, Prato Hospital)
Bariatric Surgery (Prof. Bernd Schultes, St. Gallen Hospital, Switzerland)
Metabolomics of the Mitochondrion (Prof. Roland Lill, University of Marburg, Germany)
Osteoarthritis (Prof. Brandi, University of Florence)
Krabbe disease (Dott.sa Alice Luddi, University of Siena)
Gestational diabetes (Dr. Dani, Careggi Hospital)

25. Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

26. Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra
and corresponding Follow-up
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170

27. There exist a metabolic fingerprint of celiac disease
Celiac – Healthy Subjects – Cross: predicted Potential Celiac
These alteration are present also in potential celiac subjects: so they precede the intestinal damage
Potential CD largely shares the metabonomic signature of overt CD. Most metabolites found to be significantly different between control and CD subjects were also altered in potential CD. Our results suggest early institution of GFD in patients with potential CD
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J. Proteome Res. 2010

28. http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org

29. Breast cancer metabolomics
Classification between Pre-Op and Metastatic subjects.
Accuracy ~80%
Other comparisons
NOESY
CPMG
Healthy vs
Met
Accuracy
Healthy vs
Met
Accuracy
72.67%
73.44%
Healthy vs
Post-op
Accuracy
70.00%
Healthy vs
Post-op
Accuracy
75.80%
Post vs
Met
Accuracy
74.96%
Post-op vs
Met
Accuracy
70.00% 29

30. Colorectal Cancer Metabolomics
Serum samples from 139 HS and 155 patients with mCRC, included in a prospective phase II study of 3rd line treatment with cetuximab and irinotecan
We can discriminate healthy controls from mCRC with almost 100% accuracy.
We can predict the overall survival of the patients
Cross-validated results on the Training Set:
Sensitivity : 79.9%
Specificity: 76.4%
Accuracy: 78.5%
Univariate Cox Regression Analysis for the Validation Set:
HR: 3.30
95% CI: to 5.37
P: ∙ 10-6
PLS-CA model: long survival, in blue; short survival, in yellow
Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P., Cancer Res Jan 1;72(1): Epub 2011 Nov 11 30 30 30 30

31. Heart failure metabolomics
Classification between different subgroups of Heart failure patients (1D CPMG spectra).
Sensitivity
Specificity
Accuracy
CMD vs CMS
45.52%
68.29%
61.19%
NYHA1 vs NYHA 2
61.88%
71.42%
67.71%
NYHA2 vs NYHA 3/4
73.62%
56.44%
68.04%
NYHA 1 vs NYHA 3/4
74.83%
68.55%
72.15%
Patients vs Healthy
85.11%
91.04%
87.29%
Patients are separated from healthy, but there is not any significant difference between the disease grading that could reflect the clinical severity of the disease.
Although good discrimination between healthy and HF subjects with a severe disease, if not expected, was easy to be hypothesized, a comparable good discrimination ability between healthy and HF subjects with a mild disease was unexpected and appears rather counter-intuitive. 31 31 31 31

32. Metabolomics of Melanoma
NOESY Spectra
SERUM
URINE
Sensitivity (%)
Specificity (%)
Accuracy (%)
Healthy vs. Melanoma
91.38
81.67
89.89
95.46
70.52
91.37
Stage I/II vs. Healthy
85.49
85.34
85.25
91.03
79.02
87.46
Stage III/IV vs. Healthy
88.84
91.40
89.3
85.44
80.25
82.93
Stage I/II vs III/IV
85.18
73.28
79.94
75.40
67.86
72.98 32 32

33. Fingerprint of Obesity
NW vs SO
94.0
OW vs SO
79.6
NW vs OW
69.7
NW vs OW+SO
87.8
NW+OW vs SO
84.1
The prediction of OW (stars) using the NW (green) vs SO (blue)
model classify almost all OW as SO (except two) 33 33

34. Da Vinci European BioBank

35. http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Metabolomica
L’approccio combinato di metabolomica (Prof. Claudio Luchinat) e biobanca (Prof. Paola Turano) ci rende unici in questo settore della scienza
FROM METABOLOMICS
Metabolomic analysis
Validation of
sample quality
in biobanks
Definition of
new SOPs
TO BIOBANKS
Dalla Metabolomica
Analisi Metabolomica
Controllo
Qualità di campioni
Nelle biobanche
Definizione di
Nuove SOP
Alle Biobanche
Spettro NMR di urina di un donatore sano
davincieuropeanbiobank.org

36. http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Fiorgen ha implementato una Biobanca su standard europei che è inserita nei programmi nazionali ed europei. Essa raccoglie campioni biologici (sangue, urine, biopsie) di molte malattie .
Collezioni di campioni della Biobanca:
Scompenso cardiaco (Prof. Gianfranco Gensini)
Melanoma (Prof. Nicola Pimpinelli)
Cancro alla mammella (Prof. Angelo Di Leo, e USA)
Cancro al colon (Prof. Benny V. Jensen, Danimarca)
Disturbi alla prostata (Prof. Marco Carini)
Celiachia (Prof. Antonio Calabrò)
Osteoporosi (Prof.ssa Maria Luisa Brandi)
davincieuropeanbiobank.org

37. The Future of Medicine
Metabolomics can monitor the same individual in a multidimensional space
hepatocarcinoma
Colorectal cancer
cirrhosis
steatosis
Intestinal bowel disease
Metabolic syndrome
Healthy aging
Diabetes
Hypertension
Hearth Failure 37

38. Et interviene di questa come dicono e’ fisici dello etico, che nel principio del suo male è facile a curare e difficile a conoscere, ma, nel progresso del tempo, non l’avendo in principio conosciuta né medicata, diventa facile a conoscere e difficile a curare.
Machiavelli, Il Principe, cap. 3

39. http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Il sogno
Dotare ogni cittadino di un chip in cui sono riportati il genoma, il proteoma e il metaboloma al fine di monitorarne nel tempo lo stato di salute
davincieuropeanbiobank.org

40. From general to personalized medicine
The Future of Medicine
From general to personalized medicine 40

41. Ivano Bertini
December 6, 1940
– July 7, 2012

44. Metabolomics @CERM/CIRMMP Metabolomics Publications
Human phenotypes
Assfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M. Evidence of different metabolic phenotypes in humans. Proc Natl Acad Sci U S A 2008;105(5): (IF=9.771).
Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L. Individual human phenotypes in metabolic space and time. J Proteome Res Sep;8(9): (IF=5.460).
Cardiovascular diseases
Bernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples. J Proteome Res [Epub ahead of print] (IF=5.460).
Celiac disease
Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011 Feb 4;10(2): (IF=5.460).
Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L. The metabonomic signature of celiac disease. J Proteome Res Jan;8(1): (IF=5.460).
Ozono terapy
Travagli V, Zanardi I, Bernini P, Nepi S, Tenori L, Bocci V. Effects of ozone blood treatment on the metabolite profile of human blood. Int J Toxicol 2010;29(2): (IF=1.762).

45. Metabolomics @CERM/CIRMMP
Breast cancer
Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC, Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: A pilot study. Mol Oncol Jun 1. (IF=4.250).
Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E, Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Ann Oncol 2011 Jun;22(6): (IF=6.452).
Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011 Jul;43(7): Review. (IF=4.956).
Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: available results, current research projects in breast cancer, and future applications. J Clin Oncol Jul 1;25(19): (IF=18.970).
Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol. 2007;18 Suppl 12:xii8-14. Review. (IF=6.452).
Colorectal Cancer
Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL, Turano P. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res Jan 1;72(1): (IF=8.234).

46. Metabolomics @CERM/CIRMMP
Peridontal diseases
Mario Aimetti, Stefano Cacciatore, Antonio Graziano and Leonardo Tenori. Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics; Online First™ (IF=3.608).
Standard Operating Procedures
Bernini P, Bertini I, Luchinat C, Nincheri P, Staderini S, Turano P. Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR Apr;49(3-4): (IF=3.047).
The future of medicine
Bertini I; Luchinat C; Tenori L. Metabolomics for the future of personalized medicine through information and communication technologies. PERSONALIZED MEDICINE Volume: 9 Issue: 2 (IF=0.783).

47. Our interest in metabolomics
Metabolic signature of individuals:
Metabolic phenotype
Metabolic signature of diseases
Coeliac disease
tumor  metastasis
heart failure, pulmonary diseases,etc…
Metabolites and biobank samples
Sensitive reporters of stability
Assess sample preparation and preanalytical procedures
SOP

48. Metabolomics steps Handling and preparation of samples NMR analysis
Metabolites identification
Statistical analysis
Data processing and bucketing 48 48 48

49. BioBank Project Collect Store Processing Distribute
Biological samples for scientific research

50. The need for individual metabolomic screening
The Future of Medicine
The need for individual metabolomic screening
We are proposing to collect individual metabolomics data for a large screening of the Tuscany population 50

51. The FiorGen Foundation

52. How was FiorGen born
FiorGen Foundation, a “non-profit organization of social utility” (ONLUS), was founded in 2002, with the purpose of favoring scientific, cultural and social development.
FiorGen Foundation is the result of a strong link between different scientific actors such as the Magnetic Resonance Center (CERM) of the Scientific Campus of Sesto Fiorentino and the Biomedical Campus of Careggi, which has been supported by the Chamber of Commerce, Industry and Handicrafts of Florence and the Ente Cassa di Risparmio of Florence.

53. ADMINISTRATION COUNCIL
Governing Bodies
ADMINISTRATION COUNCIL
Vasco Galgani (President)
Calogero Surrenti (Vicepresident)
Gianni Amunni
Paolo Asso
Lucia Banci
Francesco Barbolla
Ivano Bertini
Gianfranco Gensini
Claudio Luchinat
SCIENTIFIC COMMITTEE
Ivano Bertini (President)
Rosanna Abbate
Andrea Galli
Maurizio Genuardi
Cristina Nativi

54. Fund Raising CF: 94100210486 Campaign "Adopt a Researcher"
Charity auction “Art and Solidarity for the research”
CF:

55. Communication
Newsletter FiorGenews
n n n n.4

61. Research Areas of FiorGen
Research Area 1: Bersagli e farmaci antitumorali
Agonisti di recettori nucleari nella modulazione della crescita ed invasività tumorale
Delezione organo specifica del recettore ARP-1 in modelli murini
Research Area 2: Fisiopatologia e farmacogenetica delle malattie cardiovascolari
Progetto Malattia Aneurismatica e Carotidea
Progetto variabilità nella risposta alla terapia antiaggregante (aspirina e clopidogrel)
Research Area 3: Origine malattie genetiche
Studio delle basi genetiche della predisposizione a neoplasie umane
Studi sull'origine della Sclerosi Laterale Amiotrofica
Caratterizzazione strutturale della proteina beta amiloide coinvolta nel morbo di Alzheimer
Research Area 4: Metabolomica
Research Area 5: BioBanca da Vinci European BioBank - daVEB
Research Area 6: Melanoma: nuovi possibili biomarcatori di diagnosi e progressione